Launch offer · 47% off

The whole course for $79. For now.

Launch pricing is limited to the first 100 students — 100 seats are left. After that the price goes back to $149. One payment unlocks every lesson, prompt, exercise, and capstone, plus all future updates.

132
Lessons: 15
Modules: ~23h
Reading

Launch offer · 47% off

Complete course

Lifetime access

$79$149USD, one-time

You save $70. Launch price for the first 100 students only.

100 of 100 launch seats leftthen $149

All 132 lessons across 15 modules
Hundreds of type-checked code examples
A hands-on exercise in every lesson
6 complete capstone builds with code
Progress tracking across devices
Every future update, included

30-day money-back guarantee. If it's not for you, email us for a full refund.

What's inside

The full curriculum, module by module.

00Start HereYour on-ramp to building with AI6 lessons · 54 min

Get oriented: what makes something an AI product, the tools builders actually use in 2026, a working setup, and your first AI feature shipped in under half an hour. Module overview →

01LLM Fundamentals for BuildersWhat you need to know about models to build on them8 lessons · 72 min

The working knowledge of language models a builder actually needs: how text is generated, tokens and context, the anatomy of an API call, output controls, reasoning models, failure modes, and how provider APIs and SDKs differ. Module overview →

02Prompting & Context for AppsPrompts that hold up in production, not just in a chat window9 lessons · 96 min

Prompting for software is different from prompting in a chat app: your prompt runs thousands of times on inputs you never saw. Learn to write, template, chain, version, and debug prompts as product code. Module overview →

03Building Core AI FeaturesThe everyday features users expect from modern software10 lessons · 105 min

Build the AI features that show up in almost every product — streaming chat, summarization, extraction, classification, transformation, inline writing help, natural-language queries, and background jobs — inside a real Next.js app. Module overview →

04Structured Outputs & Tool UseGetting typed data out and letting models call your code8 lessons · 83 min

Make model output reliable enough to drive software: schema-constrained outputs with Zod and Pydantic, validation and repair, tool use for in-app features, generative UI, and where MCP fits into a product. Module overview →

05Embeddings, Search & RAGGrounding answers in your own data12 lessons · 125 min

Build retrieval into real products: embeddings and vector storage, semantic and hybrid search, document ingestion and chunking, reranking, grounded answers with citations, freshness and permissions, and how to measure whether retrieval works. Module overview →

06Choosing, Routing & Running ModelsThe right model for each job — hosted, open, or local9 lessons · 94 min

Pick models feature by feature, route between them, add gateways and fallbacks, and run open-weight models locally, on your own GPUs, or in the browser — plus fine-tuning and distillation, and staying portable. Module overview →

07Multimodal AI: Vision, Audio & ImagesFeatures that see, hear, speak, and draw9 lessons · 90 min

Add images, documents, audio, and video to your product: vision input, document understanding, image generation and editing, speech-to-text, text-to-speech, realtime voice, video, and multimodal search — plus the media pipelines behind them. Module overview →

08AI UX & Product DesignInterfaces people understand, trust, and keep using9 lessons · 88 min

Design AI features people actually adopt: choosing the right interface beyond the chat box, designing for uncertainty and errors, perceived speed, user control, onboarding, feedback, trust and disclosure, accessibility, and rapid prototyping. Module overview →

09Evals & Quality for AI FeaturesKnowing — not hoping — that your feature works9 lessons · 97 min

A practical quality system for AI features: define quality, read outputs with error analysis, build golden datasets from real usage, write code-based and model-graded checks, evaluate extraction and RAG, and run evals in development, CI, and production. Module overview →

10Cost, Latency & ScaleAI features that are fast and pay for themselves9 lessons · 97 min

Understand and control the economics of AI features: reading your bill, unit economics, prompt caching, response caching, batch processing, latency optimization, rate limits and per-user budgets, token efficiency, and scaling workloads. Module overview →

11Safety, Privacy & Responsible AIShipping AI features you can stand behind9 lessons · 92 min

Protect users, data, and your business: risk assessment, prompt injection in apps, moderation, PII and provider data policies, securing model output, abuse and denial-of-wallet, AI regulation, copyright and provenance, and pre-launch red-teaming. Module overview →

12Deploying, Operating & Selling AI ProductsFrom working feature to a product people pay for10 lessons · 106 min

Deploy and run AI features in production — architecture, hosting and timeouts, long-running workflows, tracing, rollouts, incidents — then turn them into a business: pricing, positioning, metering and billing, and launching. Module overview →

13No-Code & Low-Code AI BuildingBuild useful AI tools without writing an app8 lessons · 77 min

For non-developers and fast-moving builders: shareable assistants, prompt-to-app builders, automation platforms, AI in spreadsheets, no-code knowledge bots, shipping safely, and knowing when to graduate to code. Module overview →

14Capstone ProjectsBuild complete AI products end to end7 lessons · 102 min

Put everything together in guided builds of complete AI products — an AI feature for a SaaS app, a RAG knowledge app, a multimodal expense app, an AI-powered internal tool, a content product with evals, and a no-code AI product — then plan what's next. Module overview →

Frequently asked questions

Do I need to know how to code?

For most of the course, yes — basic JavaScript or TypeScript. Code is TypeScript-first, with Python where it fits. If you don't code, the Start Here module, the LLM fundamentals, the AI UX and product modules, and the entire No-Code & Low-Code module (plus a no-code capstone) are written for you, and the rest will still teach you how AI products work and what to ask of your developers.

What exactly do I get?

Lifetime access to all 132 lessons across 15 modules (about 23 hours of focused reading), type-checked TypeScript examples, reusable prompts, hands-on exercises, 6 complete capstone builds, progress tracking, and every future update to the course.

Is this a subscription?

No. It's a single one-time payment with lifetime access. No recurring charges, ever.

Is the launch price really limited?

Yes. The $79 launch price applies only to the first 100 students. The seat counter on the site is live and counts real purchases. When the seats are gone, the price goes back to $149 automatically.

Can I try it before buying?

Yes. 8 lessons are completely free, including the entire Start Here module, how LLMs generate text, and building a streaming chat feature. No account required.

Which models and tools does the course use?

Code examples default to the Anthropic API (Claude 5 models) with TypeScript, and the course also covers the OpenAI and Gemini APIs, the Vercel AI SDK, Next.js, Postgres with pgvector, open-weight models via Ollama and vLLM, and Stripe for billing. Lessons focus on principles that transfer, and show where providers differ.

Will I need to pay for AI tools too?

You'll want a small amount of API credit with at least one model provider. Most exercises use small, inexpensive calls — a few dollars covers the build exercises if you follow the cost tips we teach — and several lessons show how to run open models locally for free.

How is this different from the Agent Builder Course?

They're sister courses with no overlapping lessons. The Agent Builder Course teaches you to use and build AI agents — coding agents, the agent loop, MCP servers, multi-agent systems. The AI Builder Course teaches you to build AI features and products: chat, search, RAG, extraction, multimodal, AI UX, evals, cost, and selling what you build. Where this course touches agents, it links to the other one.

How is this different from free YouTube videos and blog posts?

It's a complete, ordered path instead of scattered tips: each lesson builds on the last, every concept comes with a practical exercise, and the later modules (AI UX, evals, cost, safety, operations, pricing) cover what most tutorials skip — the parts that turn a demo into a product people trust and pay for.

How long does it take?

Most people finish the core modules in two to three weeks at 30–45 minutes a day. Every lesson stands on its own, so you can also jump straight to what you need.

Is the course kept up to date?

Yes. Models and SDKs change fast, and lessons are revised as they do — the current edition was checked against the November 2026 SDKs and models. Updates are included in your one-time purchase.

What if it's not for me?

If the course isn't right for you, email support@aibuildercourse.com within 30 days of purchase for a full refund.

How do I sign in after buying?

You're signed in automatically after checkout. On any other device, enter the email you purchased with on the sign-in page and we'll send you a one-click sign-in link — no password to remember.

Can I buy for my team?

Yes — email support@aibuildercourse.com with the number of seats and we'll set you up with team access and an invoice.